Piyush Rai, Hal Daume III

University of Utah; University of Maryland, College Park

Nonparametric Bayesian Sparse Hierarchical Factor Modeling and Regression

8:45pm - 12:00am Monday, December 08, 2008

This is part of the Posters which begins at 20:45 on Monday December 8, 2008

M19

We propose a nonparametric Bayesian sparse factor analysis model that accounts for uncertainty in the number of factors and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems in gene-expression analysis.